Quadrat Analysis_RW_Thomas

68 in order to test the null hypothesis that there is

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Unformatted text preview: ence between the frequency array shown in Fig.2(ii)a and the predicted Poisson probabilities, the data in Table 1 was arranged for the 2 test. Following the grouping criterion it is necessary to merge the frequencies for m 2,3,4 into a single class of m '2. The results of the subsequent 2 test are shown in Table 2. The test is made at the o = .05 significance level which means that the prob- The Kolmogorov-Smirnov D statistic x x Kolmogorov-Smirnov D statistic. The statistic measures goodness-of-fit by testing the maximum deviation between the predicted cumulative frequency distribution and the observed cumulative frequency distribution for a significant difference. Assuming that each observation (mi) is part of a random quadrat sample of size n, then the magnitude of the deviation is dependent solely on n, such that the statistic D may be defined as 15 at a predefined significance level. Tables for critical values of D at a variety of significance levels may be found in Siegel (1956) and Lindgren (1975). The test has been applied to the observed and Poisson data listed in .20 significa...
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This note was uploaded on 02/15/2012 for the course GEO 6938 taught by Professor Staff during the Summer '08 term at University of Florida.

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